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A new algorithm for linearly reconstructing the infinite homography matrix and intrinsic parameter matrix of a camera

机译:线性重构相机单应性矩阵和内在参数矩阵的新算法

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By deriving the formula to directly determine the infinite homography matrix from a pair of fundamental matrixes, a new linear restoration algorithm of the homography matrix of the plane at infinity from feature point-pair sets extracted from three views under a pair of linearly independent motions is developed in this paper. Then, in terms of the similar decomposition of the infinite homography matrix, we prove that as soon as an additional orthogonal constraint to the pair of linearly independent motions is imposed on, the intrinsic parameter matrix of the camera to be self-calibrated can be linearly and uniquely determined. So, a new linear self-calibration algorithm from feature point-pair sets extracted from three views under a pair of orthogonal motions is successfully developed. Experiments show that the new algorithm has the advantages of simple realization, high computation speed, excellent restoration precision and strong antinoise ability.
机译:通过从一对基本矩阵推导直接确定无限单应性矩阵的公式,在一对线性独立运动下,从三个视图中提取的特征点对对中的无穷大平面单应性矩阵的线性恢复新算法是本文开发。然后,根据无限单应性矩阵的类似分解,我们证明,只要对这对线性独立的运动施加附加正交约束,就可以线性地校准要校准的摄像机的固有参数矩阵并且是唯一确定的因此,成功地开发了一种新的线性自校准算法,该算法可以在一对正交运动下,从三个视图中提取的特征点对对集合中提取特征。实验表明,该算法实现简单,计算速度快,恢复精度高,抗噪能力强。

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